Large-scale value-based non-linear models often require large numbers of decision variables and constraints (e.g., over a million). Heuristic algorithms, such as Multi-objective Evolutionary Algorithms (MOEAs), may fail when they have such a large number of decision variables and constraints. Often times in these MOEAs, the computational bandwidth needed to evaluate whether a potential solution violates a constraint may be relatively high. In some cases, determining whether potential solutions violate constraints may require similar or even more computational bandwidth than evaluations of potential solutions on the basis of one or more objectives.